LinguaKit: a Big Data-based multilingual tool for linguistic analysis and information extraction
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Abstract
This paper presents LinguaKit, a multilingual suite of tools for analysis, extraction, annotation and linguistic correction, as well as its integration into a Big Data infrastructure. LinguaKit allows the user to perform different tasks such as PoS-tagging, syntactic parsing, coreference resolution (among others), including applications for relation extraction, sentiment analysis, summarization, extraction of multiword expressions, or entity linking to DBpedia. Most modules work in four languages: Portuguese, Spanish, English, and Galician. The system is programmed in Perl and is freely available under a GPLv3 license.
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Keywords
Bilingual| Information Extraction| Big Data| Sentiment Analysis| Postage| Relation Extraction| Syntactic Analysis| Multi-word| Basis Of Analysis| Fault-tolerant| Analysis Module| Disambiguation| State Machine| Tokenized| Related Entities| Input Text| List Of Pairs| Basic Module| Big Data Technology| Proper Nouns| Phonetic Transcription| Keyword Extraction| Semantic Annotation| Lemmatization| Apache Spark| Language Identification
Bibliographic citation
P. Gamallo, M. Garcia, C. Piñeiro, R. Martinez-Castaño and J. C. Pichel, "LinguaKit: A Big Data-Based Multilingual Tool for Linguistic Analysis and Information Extraction," 2018 Fifth International Conference on Social Networks Analysis, Management and Security (SNAMS), Valencia, Spain, 2018, pp. 239-244, doi: 10.1109/SNAMS.2018.8554689.
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This work has been supported by MINECO (TIN2014-54565-JIN, FFI2014- 51978-C2-1-R), MICINN (IJCI-2016-29598), Xunta de Galicia (ED431G/08), European Regional Development Fund (ERDF), and by two BBVA Foundation Grants for Researchers and Cultural Creators (2016 and 2017).
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